Simplifying Complexity is a podcast about the underlying principles of complex systems. On the show, we explore the key concepts of complexity science with expert minds from around the world. Each episode focuses on an interview where we break down a specific concept in detail.
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episode 5: Modelling the spread of coronavirus in the lungs
How do you model a complex system? Traditionally we would observe how the system is behaving and create equations to mimic this behaviour, but this doesn't work for complex systems. This is because the interactions between agents in a complex system can significantly impact the system's overall behaviour.
In today's episode, Melanie Moses, Professor of Computer Science at the University of New Mexico, will answer this question. She'll introduce us to agent-based models, which are very different to how we traditionally model systems. More specifically, Melanie will explain how she used agent-based models to understand the spread of coronavirus in the lungs.
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